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Hey guys, this week we’re talking about probably the most overused phrase in the start-up world: product-market fit (PMF). More specifically, how to measure whether you are indeed finding PMF or just winning customers.
When Chris McCall moved from ocean robotics to aerial drones, he made a mistake that nearly every first-time founder makes: he optimized for metrics that looked good to investors rather than metrics that mattered to customers.
Building Fotokite, a company creating tethered drone systems for firefighters and first responders, taught him that the clearest signal of product-market fit often comes from metrics that have nothing to do with sales.
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What usually happens
Early-stage founders often fall into the "revenue trap"—believing that paying customers automatically validates product-market fit. But McCall's experience with first responders revealed a more nuanced truth:
Payment indicates interest. Usage indicates necessity.
For Fotokite, the difference was stark. A broadcaster might purchase one system to test (revenue metric: +1 customer), but only use it once every four outings. A fire department may purchase one, but deploy it every single mission they have.
The revenue metric is the same (upfront hardware sold + recurring revenues), but you’ve found product market fit with one type of customer, and not the other.
The usage data told the real story. When firefighters consistently chose to deploy Fotokite systems during actual emergencies that revealed something no sales conversation could: the product had become indispensable.
"From the first day, we made sure to get it into anybody's hands, put this in the hands of a four or five year old, and you'll understand whether it's easy to use or not."
This obsession with actual usage over theoretical demand became their competitive advantage.
The metric that matters
"Over the last 12 months, we saw about 150,000 missions flown in public safety and first responder operations, we track that really closely by being really close with our customer. If that continues growing at the rate that it has been, that's a really exciting future for us."
150,000 missions flown. Not dollars of revenue, not units sold—actual deployments solving real problems in emergency situations.
This wasn't always their North Star. Like most hardware startups, Fotokite initially tracked traditional metrics: development milestones, manufacturing costs, and early sales numbers. But McCall discovered something crucial: these financial metrics were lagging indicators, while usage metrics were leading indicators of sustainable growth.
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Hidden in plain sight
Traditional startup advice says to optimize for revenue and growth metrics early. But McCall's journey suggests a different approach for hardware and B2B companies: establish usage-based product-market fit before scaling revenue-based growth.
Consider Fotokite's evolution:
Phase 1 (Revenue-Focused): Broad market approach targeting consumers, broadcasters, and professionals. Revenue came in, but usage patterns were inconsistent.
Phase 2 (Usage-Focused): Pivot to public safety after noticing firefighters deployed systems most frequently and intensively. Revenue initially dropped, but usage exploded.
Phase 3 (Sustainable Growth): Usage intensity drove word-of-mouth referrals, repeat purchases, and market expansion. Revenue followed organically.
"We needed quite a bit to learn about how our focus customers purchase equipment and roll them into their standard operating procedures"
The key insight: procurement processes matter less than deployment frequency.
Leading vs lagging
McCall's experience reveals a framework for early-stage metric prioritization:
Optimise leading indicators first:
Usage intensity per customer
Problem-solving frequency
Customer outcome achievement
Operational integration depth
Track lagging indicators second:
Revenue per customer
Customer acquisition cost
Lifetime value
Growth rate
"What we ended up finding out over time was with a tether, we could deliver even more value"
This discovery came from watching how customers actually used the product, not from financial analysis.
This approach requires founder discipline. Early investors often pressure for revenue metrics, but McCall learned that premature revenue optimization can mask weak product-market fit.
"We were always working towards the next external milestone to show the traction we needed to get the next financing"
But the most compelling traction story became usage data: departments deploying systems multiple times per week, expanding use cases, and requesting additional capabilities.
When Australia's first responders reached out "for years" before Fotokite could enter that market, it wasn't because of marketing campaigns—it was because usage stories from other countries demonstrated clear value.
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What this meant for Fotokite
Companies that nail usage-based product-market fit early build natural competitive advantages:
Customer intimacy from understanding actual workflows
Product stickiness from solving real operational problems
Organic growth from word-of-mouth within user communities
Pricing power from demonstrable ROI
"We're getting pulled into markets. We're not pushing ourselves into those markets"
Being pulled rather than pushing—that's what happens when usage metrics prove indispensable value before revenue metrics prove scalable business models.
Key Takeaway: Before optimizing for revenue growth, optimize for usage intensity. The strongest predictor of long-term success isn't how much customers pay, but how often they can't operate without you.
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See you next week!
Rahul & Aryaman
